I am very surprised at the resilience of the Venezuelan character. With Chavez destroying the country, the economy in its third year of recession and the next two years which promise to be of continued political strife, Venezuelans are still happy. They are happier than Brazilians even if the Venezuelans are poorer and will only get poorer still. I guess that nice beaches and good looking women are too powerful a drug.

Without a definition of the Y-axis "Mean life satisfaction" the charts and the conclusions drawn from them are, I suggest, no more useful than the pattern in the snowflake that may be resting agaisnt your window or some tea leaves in your mug.

And how do you measure "happiness" anyway? What makes me happy is quite likely to be different from what makes you happy in many cases.

And is that really Angus Deaton in the Sources citation?

This whole idea of happiness measuring really is a nonsense. So wooly that it will be the servant of the agenda of the person(s) doing the measuring. Which is I suspect the point.

Well as someone said, probably that well know comedian and “graphist” Angus Deaton (for it is he that is author of charts), there are lies, damned lies and graphs. Especially graphs that combine the dismal science with tortured manipulation of data. But on a more serious note: I do think we in the developed have become obsessed with equating money with happiness. Dont get me wrong: it is important to have a decent income but a kind of mass psychology is operating here that forces us to believe we will never be happy unless we consume ever more, earn ever more .

I'm quite surprise about the weak aproach of this article. It's a well known fact that the correlation is not even close to be linear, but it moves between a bounded area: if you don't have enough money (lower bound), you are unhappy (poor countries are full of that: no health system, not enough food etc...); on the other hand, too much money is correlated with a lack of time, wich cause unhappiness too (upper bound). Therefore is the first reason why this article is ridiculously inaccurate.
And finally; this kind of aproximation is useless. It's a childish manipulation of data. It doesn't change the underlying phenomenon (even being absurdly flexible with the bounded set point of view). I'm quite disappointed, the Economist deserves better...

If a person is poor, a little money can make him/her feel happy and excited, but for a person who is rich and never experiences any financial difficulties, it needs a large amount of money to achieve the same effect.

The great flaw in the argument presented above is that correlation doesn't imply causality. There may be a lot of reasons why Brazilians, that live in a poor, corrupt and violent country are almost as happy as people living in the USA or Britain.
There is a more robust technic, called Granger causality teste, that is used to measure if an event is the cause of a observed phenomenon.

To answer the question "Why log scale?"(surprisingly disappointing, Economist did not do it; there was one answer in the beginning, but not well defined and the question pops up again):

The log scale is used due to the decreasing marginal utility of income (as somebody explained earlier, an Euro more when I am poor makes me more happy than an Euro more when I am rich). Correlation measures only linear relationship (like Y=a+bX - here having Y as happiness and X as income would result in "an Euro makes me equally happy independent of how rich I am"). Here the assumption is that we have a concave relationship due to the decreasing marginal utility (the function Y=a+b*ln(X)) - you can very nicely see the concavity in the first graph - and the second graph adjsts it into the linear function (Y=a+b*ln(X)) so that estimating it is easier (any standard software, even new Excel versions can do it) - however, in the style of the Economst, most of the relevant numbers are ommited and there is no indication of what is the blue line in the second graph - for sure not Least Squares, what?

Of course, as always with statistics, one should always be careful with what is the cause and what is the effect (or if there is causality both ways or from a third factor). And I also think that with playing with statistics one can "prove" almost anything to a lay person. Including another things like the earlier proposed former GDPs, Gini, health etc. could potentially improve the model. And definitely agree that without saying how exactly is "mean life satisfaction" measured the graphs are almost useless.

One more thing: Would like to see the same information for nominal GDP.

>happyfish wrote:
>The Western notion of happiness is to make plenty of money by hook and
>crooks, and then topped it with a celebrity spouse on the tow or the
>arm.

Going be what I have seen in China and SE Asia, on that count, the orientals have out-Westernized the West (making lots of money by any means possible and hiving the flashiest floozie on one's arm seems to be the basic social requirement in China and surrounding countries)

Scientists studying happiness? What does a data driven, rigid, severely
limited means of examining the world have to say regarding something
so subtle and elusive? Can't it be left to those who have made some
progress on the subject, the philosophers and prophets, the great
leaders, even the occasional psychologist?. Science is just so
clumsy when it tackles these things, it is embarrassing.